HELP! Training assistive indoor agents to ask for assistance via imitation learning
Today people use personal digital assistants for help with scheduling, playing music, turning on or adjusting other devices, and answering basic questions such as “What time’s the game on?” or “Where’s the nearest hardware store?”…
All Data AI with Dr. Andrew Fitzgibbon
You may not know who Dr. Andrew Fitzgibbon is, but if you’ve watched a TV show or movie in the last two decades, you’ve probably seen some of his work. An expert in 3D computer…
MazeExplorer [1.0.0]
MazeExplorer is a customisable 3D benchmark for assessing generalisation in Reinforcement Learning. It is based on the 3D first-person game Doom and the open-source environment VizDoom. This repository contains the code for the MazeExplorer Gym…
VNLA via Imitation Learning with Indirect Intervention
We present Vision-based Navigation with Language-based Assistance (VNLA), a grounded vision-language task where an agent with visual perception is guided via language to find objects in photorealistic indoor environments. The task emulates a real-world scenario…
2019 Dissertation Grant recipients embarking on diverse paths to scientific and societal impact
I’m pleased to announce the winners of the 2019 Microsoft Research Dissertation Grants. Each dissertation grant provides up to $25,000 in funding to doctoral students at North American universities who are underrepresented in the field…
AI for Earth’s Land Cover Mapping
High-resolution land cover mapping is a process of assigning land use labels, such as “impervious surface,” or “tree canopy” to each pixel in high resolution (<1m) aerial or satellite imagery. Such maps are an essential…